Show simple item record

dc.contributor.authorNagoor, Omniah H.en_US
dc.contributor.authorBorgo, Ritaen_US
dc.contributor.authorJones, Mark W.en_US
dc.contributor.editorTao Ruan Wan and Franck Vidalen_US
dc.date.accessioned2017-09-21T07:22:52Z
dc.date.available2017-09-21T07:22:52Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-050-5
dc.identifier.urihttp://dx.doi.org/10.2312/cgvc.20171280
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/cgvc20171280
dc.description.abstractThe choice of a mapping from data to color should involve careful consideration in order to maximize the user understanding of the underlying data. It is desirable for features within the data to be visually separable and identifiable. Current practice involves selecting a mapping from predefined colormaps or coding specific colormaps using software such as MATLAB. The purposes of this paper are to introduce interactive operations for colormaps that enable users to create more visually distinguishable pixel based visualizations, and to describe our tool, Data Painter, that provides a fast, easy to use framework for defining these color mappings. We demonstrate the use of the tool to create colormaps for various application areas and compare to existing color mapping methods. We present a new objective measure to evaluate their efficacyen_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.subjectVisual analytics
dc.subjectVisualization toolkits
dc.titleData Painter: A Tool for Colormap Interactionen_US
dc.description.seriesinformationComputer Graphics and Visual Computing (CGVC)
dc.description.sectionheadersColours and Bitmaps
dc.identifier.doi10.2312/cgvc.20171280
dc.identifier.pages69-76


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record